*****************************************************************
*****************************************************************
*****                                                       *****
*****       Mona Morgan-Collins (Durham University, UK)     *****
*****       Grace Natusch (The Civil Service, UK)           *****
*****       Contact: mona.morgan-collins@durham.ac.uk       *****
*****                                                       *****
*****       At the Intersection of Gender and Class:        *****
***** How Were Newly Enfranchised Women Mobilized in Sweden?*****
*****                                                       *****
*****           Comparative Political Sudies                *****
*****                                                       *****
*****           Replicating Analyses in the Paper           *****
*****                                                       *****
*****************************************************************
*****************************************************************


*********************************
*Table 1: Sampled Elections
*********************************

*nothing to replicate


*********************************
*Table 2: Data Structure: Properties, Families and Electors
*********************************
use dta\sod2134, clear                       //using sod2134 data set

*statistics on properties
preserve
gen entry = 1
collapse (mean) entry, by(year property_id)
by year: tab entry                           //number of properties by year
restore
preserve
gen entry = 1
collapse (sum) entry, by(year property_id)
by year: sum entry , det                     //mean electors per property by year
restore

*statistics on families
preserve
gen entry = 1 
collapse (mean) entry, by(year family_id)    //number of families by year
by year: tab entry
restore
preserve
collapse (mean) property_id, by(year family_id)
bys property_id: gen housen = _n
bys year property_id: egen housen_max = max(housen)
collapse (mean) housen_max, by(property_id year)
bys year: sum housen_max , det               //mean number of families per property by year
restore

*statistics on electors
preserve
gen entry = 1
collapse (sum) entry, by(year)
by year: tab entry                           //number of electors by year
restore
preserve
gen entry = 1
collapse (sum) entry, by(year family_id)     //mean electors per family
by year: sum entry
restore


******************************************************************
*Figure 1: Class Composition of Neighbors
******************************************************************
use dta\sod2134, clear                       //using sod2134 data set

*sub-figure a: working class
#delimit ; 
twoway hist tworkp_pc if year==1921 & class_wife==3, lcolor(black) color(black) percent w(2)  || hist tworkp_pc if year==1934 & class_wife==3, lcolor(gray) color(none) percent w(2)  ||
, ytitle(% Working class, size(vlarge)) ylabel(0(10)40 , labsize(vlarge))  xtitle("% Working class neighbors", size(vlarge)) xlabel(0(20)100, labsize(vlarge))  
legend(off) scheme(s1color) ysize(5) ; 
#delimit cr

*sub-figure b: upper and middle class
#delimit ; 
twoway hist tupmidp_pc if year==1921 & class_wife<=2 & class_wife>=1, lcolor(black) color(black) percent w(2) || hist tupmidp_pc if year==1934 & class_wife<=2 & class_wife>=1, lcolor(gray) color(none) percent w(2)  ||
, ytitle(% Upper & middle class, size(vlarge)) ylabel(0(10)40 , labsize(vlarge))  xtitle("% Upper & middle class neighbors", size(vlarge)) xlabel(0(20)100, labsize(vlarge))  
legend(off) scheme(s1color) ysize(5); 
#delimit cr


******************************************************************
*Figure 2: Turnout by Gender, Class & Election in Södertälje
******************************************************************
use dta\sod2134, clear                       //using sod2134 data set

*Sub-Figure a: Municipal 1921
#delimit ; 
graph bar voted_mf voted_mm if year==1921, over(classw_rec  , relabel(1 "Dep" 2 "UpMid" 3 "Work" ) 
label(labsize(huge))) blabel(bar, size(large) format(%9.2f)) ytitle("Turnout", size(huge)) ylabel (0(0.2)0.8 , labsize(huge) nogrid) 
box(1, color(gray) ) box(2, color(gs4) ) marker(1 , mcolor(gray)) title("",  size(vlarge))  legend(off) scheme(s1color) ysize(5) ; 
#delimit cr

*Sub-Figure b: County 1921
#delimit ; 
graph bar voted_cf voted_cm if year==1921, over(classw_rec  , relabel(1 "Dep" 2 "UpMid" 3 "Work" ) 
label(labsize(huge))) blabel(bar, size(large) format(%9.2f)) ytitle("Turnnout", size(huge)) ylabel (0(0.2)0.8 , labsize(huge) nogrid) 
box(1, color(gray) ) box(2, color(gs4) ) marker(1 , mcolor(gray)) title("",  size(vlarge))  legend(off) scheme(s1color) ysize(5) ; 
#delimit cr

*Sub-Figure c: Municipal 1934
#delimit ; 
graph bar voted_mf voted_mm if year==1934, over(classw_rec  , relabel(1 "Dep" 2 "UpMid" 3 "Work" ) 
label(labsize(huge))) blabel(bar, size(large) format(%9.2f)) ytitle("Turnout", size(huge)) ylabel (0(0.2)0.8 , labsize(huge) nogrid) 
box(1, color(gray) ) box(2, color(gs4) ) marker(1 , mcolor(gray)) title("",  size(vlarge))  legend(off) scheme(s1color) ysize(5) ; 
#delimit cr


******************************************************************
*Figure 3: Average Neighbor Effects By Class and Gender 
******************************************************************
use dta\sod2134, clear                       //using sod2134 data set

*Sub-Figure a: Working Class
gen w21m = workXtworkp_pc
gen w21c = workXtworkp_pc
gen w34m = workXtworkp_pc
gen w21mf = workXtworkp_pc
gen w21cf = workXtworkp_pc
gen w34mf = workXtworkp_pc
gen w21mm = workXtworkp_pc
gen w21cm = workXtworkp_pc
gen w34mm = workXtworkp_pc

quietly reg voted_munic  i.worker w21m   C_age C_age2  i.married   i.property_id, cluster(property_id), if right_munic==1  & year==1921   
quietly estimates store w21m
quietly reg voted_county i.worker w21c   C_age C_age2 i.married   i.property_id, cluster(property_id), if right_county==1 & year==1921   
quietly estimates store w21c
quietly reg voted_munic  i.worker w34m   C_age C_age2  i.married   i.property_id, cluster(property_id), if right_munic==1  & year==1934  
quietly estimates store w34m
quietly reg voted_munic  i.worker w21mf   C_age C_age2  i.married   i.property_id, cluster(property_id), if right_munic==1  & year==1921   & female==1 
quietly estimates store w21mf
quietly reg voted_county i.worker w21cf   C_age C_age2  i.married   i.property_id, cluster(property_id), if right_county==1 & year==1921   & female==1 
quietly estimates store w21cf
quietly reg voted_munic  i.worker w34mf   C_age C_age2  i.married   i.property_id, cluster(property_id), if right_munic==1  & year==1934   & female==1 
quietly estimates store w34mf 
quietly reg voted_munic  i.worker w21mm   C_age C_age2  i.married   i.property_id, cluster(property_id), if right_munic==1  & year==1921   & female==0  
quietly estimates store w21mm
quietly reg voted_county i.worker w21cm   C_age C_age2  i.married   i.property_id, cluster(property_id), if right_county==1 & year==1921   & female==0 
quietly estimates store w21cm
quietly reg voted_munic  i.worker w34mm   C_age C_age2  i.married   i.property_id, cluster(property_id), if right_munic==1  & year==1934   & female==0 
quietly estimates store w34mm
 
#delimit ;                                      
coefplot 
(w21m, msym(o) mcolor(red) mlabcolor(red) msize(large) ciopts(lcolor(red) lwidth(midthick)   ) )
(w21c, msym(o) mcolor(red) mlabcolor(red) msize(large) ciopts(lcolor(red) lwidth(midthick)   ) )
(w34m, msym(o) mcolor(red) mlabcolor(red) msize(large) ciopts(lcolor(red) lwidth(midthick)   ) )
(w21mf, msym(o) mcolor(gray) mlabcolor(gray) msize(large) ciopts(lcolor(gray) lwidth(midthick)   ) )
(w21cf, msym(o) mcolor(gray) mlabcolor(gray) msize(large) ciopts(lcolor(gray) lwidth(midthick)   ) )
(w34mf, msym(o) mcolor(gray) mlabcolor(gray) msize(large) ciopts(lcolor(gray) lwidth(midthick)   ) )
(w21mm, msym(o) mcolor(black) mlabcolor(black) msize(large) ciopts(lcolor(black) lwidth(midthick)   ) )
(w21cm, msym(o) mcolor(black) mlabcolor(black) msize(large) ciopts(lcolor(black) lwidth(midthick)   ) )
(w34mm, msym(o) mcolor(black) mlabcolor(black) msize(large) ciopts(lcolor(black) lwidth(midthick)   ) )
, ylabel(-0.005(0.0025)0.005, labsize(vlarge)) ytitle("Average Neighbor Effects", size(vlarge) )  xlabel(,labsize(vlarge) ) xscale(range(0(1)10)) 
keep( w21m w21c w34m  w21mf w21cf w34mf  w21mm w21cm w34mm )  coeflabels(w21m="M21" w21c="C21" w34m="M34"   w21mf="M21" w21cf="C21" w34mf="M34"  w21mm="M21" w21cm="C21" w34mm="M34"  , angle(45)      )  
yline(0, lcolor(gray)) xline(3.5 6.5, lcolor(gray)) levels(95) scheme(s1mono) legend(off) vertical title("", size(vlarge) ) ysize(5) 
text(-0.0045 8 "Men", color(black) size(large)) text(-0.0045 5 "Women", color(gray) size(large)) text(-0.0045 2 "All", color(red) size(large)) ;
#delimit cr

*Sub-Figure b: Upper and Middle Class
gen um21m = upmidXtupmidp_pc
gen um21c = upmidXtupmidp_pc
gen um34m = upmidXtupmidp_pc
gen um21mf = upmidXtupmidp_pc
gen um21cf = upmidXtupmidp_pc
gen um34mf = upmidXtupmidp_pc
gen um21mm = upmidXtupmidp_pc
gen um21cm = upmidXtupmidp_pc
gen um34mm = upmidXtupmidp_pc

quietly reg voted_munic  i.upmid um21m   C_age C_age2  i.married   i.property_id, cluster(property_id), if right_munic==1  & year==1921   
quietly estimates store um21m
quietly reg voted_county i.upmid um21c   C_age C_age2  i.married   i.property_id, cluster(property_id), if right_county==1 & year==1921   
quietly estimates store um21c
quietly reg voted_munic  i.upmid um34m   C_age C_age2  i.married   i.property_id, cluster(property_id), if right_munic==1  & year==1934  
quietly estimates store um34m
quietly reg voted_munic  i.upmid um21mf   C_age C_age2  i.married   i.property_id, cluster(property_id), if right_munic==1  & year==1921   & female==1 
quietly estimates store um21mf
quietly reg voted_county i.upmid um21cf   C_age C_age2  i.married   i.property_id, cluster(property_id), if right_county==1 & year==1921   & female==1 
quietly estimates store um21cf
quietly reg voted_munic  i.upmid um34mf   C_age C_age2  i.married   i.property_id, cluster(property_id), if right_munic==1  & year==1934   & female==1 
quietly estimates store um34mf 
quietly reg voted_munic  i.upmid um21mm   C_age C_age2  i.married   i.property_id, cluster(property_id), if right_munic==1  & year==1921   & female==0  
quietly estimates store um21mm
quietly reg voted_county i.upmid um21cm   C_age C_age2  i.married   i.property_id, cluster(property_id), if right_county==1 & year==1921   & female==0 
quietly estimates store um21cm
quietly reg voted_munic  i.upmid um34mm   C_age C_age2  i.married   i.property_id, cluster(property_id), if right_munic==1  & year==1934   & female==0 
quietly estimates store um34mm
 
#delimit ;                                      
coefplot 
(um21m, msym(o) mcolor(red) mlabcolor(red) msize(large) ciopts(lcolor(red) lwidth(midthick)   ) )
(um21c, msym(o) mcolor(red) mlabcolor(red) msize(large) ciopts(lcolor(red) lwidth(midthick)   ) )
(um34m, msym(o) mcolor(red) mlabcolor(red) msize(large) ciopts(lcolor(red) lwidth(midthick)   ) )
(um21mf, msym(o) mcolor(gray) mlabcolor(gray) msize(large) ciopts(lcolor(gray) lwidth(midthick)   ) )
(um21cf, msym(o) mcolor(gray) mlabcolor(gray) msize(large) ciopts(lcolor(gray) lwidth(midthick)   ) )
(um34mf, msym(o) mcolor(gray) mlabcolor(gray) msize(large) ciopts(lcolor(gray) lwidth(midthick)   ) )
(um21mm, msym(o) mcolor(black) mlabcolor(black) msize(large) ciopts(lcolor(black) lwidth(midthick)   ) )
(um21cm, msym(o) mcolor(black) mlabcolor(black) msize(large) ciopts(lcolor(black) lwidth(midthick)   ) )
(um34mm, msym(o) mcolor(black) mlabcolor(black) msize(large) ciopts(lcolor(black) lwidth(midthick)   ) )
, ylabel(-0.005(0.0025)0.005, labsize(vlarge)) ytitle("Average Neighbor Effects", size(vlarge) )  xlabel(,labsize(vlarge) ) xscale(range(0(1)10)) 
keep( um21m um21c um34m  um21mf um21cf um34mf  um21mm um21cm um34mm )  coeflabels(um21m="M21" um21c="C21" um34m="M34"   um21mf="M21" um21cf="C21" um34mf="M34"  um21mm="M21" um21cm="C21" um34mm="M34"  , angle(45)      )  
yline(0, lcolor(gray)) xline(3.5 6.5, lcolor(gray)) levels(95) scheme(s1mono) legend(off) vertical title("", size(vlarge) ) ysize(5) 
text(-0.0045 8 "Men", color(black) size(large)) text(-0.0045 5 "Women", color(gray) size(large)) text(-0.0045 2 "All", color(red) size(large)) ;
#delimit cr
 
 
******************************************************************
*Figure 4: Mechanisms
******************************************************************
use dta\sod2134, clear                       //using sod2134 data set 

*sub-figure a: length of residence
gen w34mfS = workXtworkp_pc
gen w34mfL = workXtworkp_pc

quietly reg voted_munic  i.worker w34mfS   C_age C_age2  i.married   i.property_id, cluster(property_id), if right_munic==1  & year==1934   & female==1 &long13==1 &age>35
quietly estimates store w34mfS 
quietly reg voted_munic  i.worker w34mfL   C_age C_age2  i.married   i.property_id, cluster(property_id), if right_munic==1  & year==1934   & female==1 &long13==0 &age>35 
quietly estimates store w34mfN 

#delimit ;                                      
coefplot 
(w34mfS, msym(o) mcolor(red) mlabcolor(red) msize(large) ciopts(lcolor(red) lwidth(midthick)   ) )
(w34mfN, msym(o) mcolor(black) mlabcolor(black) msize(large) ciopts(lcolor(black) lwidth(midthick)   ) )
, ylabel(-0.005(0.005)0.01, labsize(vlarge)) ytitle("Average Neighbor Effects", size(vlarge) )  xlabel(,labsize(vlarge)) 
keep(w34mfS w34mfL)  coeflabels(w34mfS=">=13 yrs"  w34mfL="<13 yrs" ) xtitle("Length of Residence", size(vlarge) ) 
yline(0, lcolor(black)) levels( 95 ) scheme(s1mono) legend(off) vertical  ysize(5) offset  ;
#delimit cr

*sub-figure a: soc dem membership
gen w34mfmem = workXtworkp_pc
gen w34mfnonm = workXtworkp_pc

quietly reg voted_munic  i.worker w34mfmem   C_age C_age2  i.married   i.property_id, cluster(property_id), if right_munic==1  & year==1934   & female==1 & member34p==1 
quietly estimates store w34mfM
quietly reg voted_munic  i.worker w34mfnonm   C_age C_age2  i.married   i.property_id, cluster(property_id), if right_munic==1  & year==1934   & female==1 & member34p==0
quietly estimates store w34mfNM 

#delimit ;                                      
coefplot 
(w34mfM, msym(o) mcolor(red) mlabcolor(red) msize(large) ciopts(lcolor(red) lwidth(midthick)   ) )
(w34mfNM, msym(o) mcolor(black) mlabcolor(black) msize(large) ciopts(lcolor(black) lwidth(midthick)   ) )
, ylabel(-0.005(0.005)0.01, labsize(vlarge)) ytitle("Average Neighbor Effects", size(vlarge) )  xlabel(,labsize(vlarge)) 
keep(w34mfmem w34mfnonm)  coeflabels(w34mfmem="Yes"  w34mfnonm="No" ) xtitle("S-Woman Neighbor", size(vlarge) ) 
yline(0, lcolor(black)) levels( 95 ) scheme(s1mono) legend(off) vertical  ysize(5) offset  ;
#delimit cr

    
*************************************************************************************************
*Figure 5: Turnout by Class, Gender and the Proportion of Workers in Urban Municipalities in 1928
*************************************************************************************************
use dta\census1928, clear          //using census1928 data set

*Sub-figure a: Urban Upper Class
#delimit ;
twoway 
(line turnm_u work_pc_num  if urban=="town", mcolor(gray) lwidth(thick))    (line turnf_u work_pc_num  if urban=="town", mcolor(black) lwidth(thick))
(scatter turnm_u work_pc_num  if urban=="town", mcolor(black)  m(O))        (scatter turnf_u work_pc_num  if urban=="town", mcolor(gray)  m(O) mlab(gg_u) mlabsize(huge) mlabpos(6))
, ytitle(Turnout (%), size(huge)) ylabel(80(5)90, labsize(huge)) xtitle("Workers in a Municipalty (%)", size(huge)) xlabel(4(1)6, valuelabel  labsize(huge)) xscale(range (3.8 6.2))
title("Upper Class", size(huge)) note("", nobox) legend(off) scheme(s1mono)  text(82 5.85 "Women", color(gray) size(huge)) text(84.5 6 "Men", color(black) size(huge)) ysize(6);
#delimit cr

*Sub-figure b: Urban Working Class
#delimit ;
twoway 
(line turnm_w work_pc_num if urban=="town", mcolor(gray) lwidth(thick))   (line turnf_w work_pc_num if urban=="town", mcolor(black) lwidth(thick))
(scatter turnm_w work_pc_num if urban=="town", mcolor(black)  m(O))       (scatter turnf_w work_pc_num if urban=="town", mcolor(gray)  m(O) mlab(gg_w) mlabsize(huge) mlabpos(6))
, ytitle(Turnout (%), size(huge)) ylabel(40(20)80, labsize(huge)) xtitle("Workers in a Municipalty (%)", size(huge)) xlabel(4(1)6, valuelabel  labsize(huge)) xscale(range (3.8 6.2))
title("Working Class", size(huge)) note("", nobox) legend(off) scheme(s1mono)  text(67 5.85 "Women", color(gray) size(huge)) text(76 6 "Men", color(black) size(huge)) ysize(6);
#delimit cr

*Sub-figure c: Rural Upper Class
#delimit ;
twoway 
(line turnm_u work_pc_num if urban=="countryside", mcolor(gray) lwidth(thick))   (line turnf_u work_pc_num if urban=="countryside", mcolor(black) lwidth(thick))
(scatter turnm_u work_pc_num if urban=="countryside", mcolor(black)  m(O))       (scatter turnf_u work_pc_num if urban=="countryside", mcolor(gray)  m(O) mlab(gg_u) mlabsize(huge) mlabpos(6))
, ytitle(Turnout (%), size(huge)) ylabel(80(5)90, labsize(huge)) xtitle("Workers in a Municipalty (%)", size(huge)) xlabel(1(1)3, valuelabel  labsize(huge)) xscale(range (0.8 3.2))
title("Upper Class", size(huge)) note("", nobox) legend(off) scheme(s1mono)  text(83 2.85 "Women", color(gray) size(huge)) text(84.5 3 "Men", color(black) size(huge)) ysize(6);
#delimit cr

*Sub-figure d: Rural Working Class
#delimit ;
twoway 
(line turnm_w work_pc_num if urban=="countryside", mcolor(gray) lwidth(thick))   (line turnf_w work_pc_num if urban=="countryside", mcolor(black) lwidth(thick))
(scatter turnm_w work_pc_num if urban=="countryside", mcolor(black)  m(O))       (scatter turnf_w work_pc_num if urban=="countryside", mcolor(gray)  m(O) mlab(gg_w) mlabsize(huge) mlabpos(6))
, ytitle(Turnout (%), size(huge)) ylabel(40(20)80, labsize(huge)) xtitle("Workers in a Municipalty (%)", size(huge)) xlabel(1(1)3, valuelabel  labsize(huge)) xscale(range (0.8 3.2))
title("Working Class", size(huge)) note("", nobox) legend(off) scheme(s1mono) text(63.1 2.85 "Women", color(gray) size(huge)) text(75 3 "Men", color(black) size(huge)) ysize(6) ;
#delimit cr
 	
	
***************************************************
*Reporting satistics in the paper
***************************************************

*reporting proportion of class groups in note for figure 2
tab classw_rec

*footnote 10: proportion of ineligibles 
tab right_munic if year==1921
tab right_county if year==1921
tab right_munic if year==1934

*footnote 11: proportion of families with more than one wife
tab wifemulti

*footnote 14: proportion of agricultural workers
tab occup_cat if year==1921 //agricultural workers coded in categories: I; I_a; I_b; I_c (see Tables Appendix A3-5): (4+16+4)/4130 = 0.6%
tab occup_cat if year==1934 //agricultural workers coded in categories: I; I_a; I_b; I_c (see Tables Appendix A3-5): (24+2+17+8)/4857 = 1.1%

*proportion of neighbors who are workers as discussed in text with respect to Figure 1
sum tworkp_pc if year==1921 & class_wife==3, det                                //2482 workers in 1921, majority in majority working class properties
sum tworkp_pc if year==1934 & class_wife==3, det                                //2715 workers in 1934, majority in majority working class properties
sum tworkp_pc if year==1921 & class_wife==3 & tworkp_pc==100                    //1033 workers lives in properties with 100% working class neighbors, so 1033/2482 = 42(%) workers live in such properties
sum tworkp_pc if year==1934 & class_wife==3 & tworkp_pc==100                    //1034 workers lives in properties with 100% working class neighbors, so 1034/2715 = 38(%) workers live in such proeprties
sum tupmidp_pc if year==1921 & class_wife<=2 & class_wife>=1, det               //786 upper and middle class in 1921
sum tupmidp_pc if year==1934 & class_wife<=2 & class_wife>=1, det               //996 upper and middle in 1934
sum tupmidp_pc if year==1921 & class_wife<=2 & class_wife>=1 & tupmidp_pc==100  //49 upper and middle class lives in properties with 100% upper and middle class neighbors, so 49/786 = 6.2(%) upper and middle class live in such proeprties
sum tupmidp_pc if year==1934 & class_wife<=2 & class_wife>=1 & tupmidp_pc==100  //45 upper and middle class lives in properties with 100% upper and middle class neighbors, so 45/996 = 4.5(%) upper and middle class lives in such properties
sum tupmidp_pc if year==1921 & class_wife<=2 & class_wife>=1 & tupmidp_pc>50    //250 upper and middle class lives in properties with majority upper and middle class neighbors, so 250/786 = 31.8(%) upper and middle class live in such proeprties
sum tupmidp_pc if year==1934 & class_wife<=2 & class_wife>=1 & tupmidp_pc>50    //370 upper and middle class lives in properties with majority upper and middle class neighbors, so 370/996 = 37.1(%) upper and middle class lives in such properties

*footnote 22: single family units
preserve
collapse (mean) property_id, by(year family_id)
bys property_id: gen housen = _n
bys year property_id: egen housen_max = max(housen)
collapse (mean) housen_max, by(property_id year)
bys year: sum housen_max  if housen_max==1                                      //number of single family properties, 135 in 1921, 229 in 1934
bys year: sum housen_max , det                                                  //total number of properties  by year, 518 in 1921, 702 in 1934. In 1921, there were 135/518 = 26(%) of single family properties. In 1934, there were 229/702 = 32(%).
restore

preserve
gen elecn = 1
collapse (mean) property_id (sum) elecn, by(year family_id)
bys property_id: gen housen = _n
bys year property_id: egen housen_max = max(housen)
collapse (mean) housen_max (sum) elecn, by(property_id year)
bys year: sum housen_max  if housen_max==1                                      //number of single family properties, 135 in 1921, 229 in 1934
bys year: sum housen_max , det                                                  //total number of properties  by year, 518 in 1921, 702 in 1934. In 1921, there were 135/518 = 26(%) of single family properties. In 1934, there were 229/702 = 32(%).
keep if housen_max==1
collapse (sum) elecn, by(year)    
browse year elecn                                                               //total number of electors living in single family properties by year: 319 in 1921 and 583 in 1934                                             
restore
bys year: sum id                                                                //total number of electors by year: 4307 in 1921 and 5023 in 1934. In 1921, there were 319/4307 = 7.4(%) of electors living in single family properties. In 1934, theer were 583/5023 = 11.6(%).

*reporting effects in std. deviation in the result section
listcoeff                                                                       //run after every model reported in Figure 3

*footnote 31: S-women in properties
tab member34p if year==1934                                                     //441 (8.8%) age eligible electors lived in properties with a soc dem women member in 1934

*29% of matched electors between 1921 and 1934, as discussed in the text with respect to Figure 4a 
tab long13 if year==1934 & age>35                                                                   //29% of age eligible electors appear in both 1921 and 1934 registers

*S-women members were almost twice as likely to participate, as discussed in text with respect to Figure 4b
sum voted_munic if year==1934 & right_munic==1 & class_wife==3 & member34==0 & female==1            //14.5% percent of working class women voted in 1934
sum voted_munic if year==1934 & right_munic==1 & class_wife==3 & member34==1 & female==1            //28.6% of working class women who lived in properties with a soc dem member voted in 1934

*footnote 32: correlating S-women and length of residence
tab member34p long13 if year==1934, col r                                                           //only 8% of long term residents lived in properties with S-women


                                                                   




